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Human Saliva Proteome and Transcriptome

¹ School of Dentistry and Dental Research Institute,
² UCLA Mass Spectrometry and Proteomics Center,
³ Department of Chemistry and Biochemistry,
⁴ Department of Biological Chemistry, School of Medicine,
⁵ Jonsson Comprehensive Cancer Center,
⁶ Molecular Biology Institute;
⁷ Division of Head & Neck Surgery/Otolaryngology, School of Medicine, and
⁸ Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA 90095–1668, USA

^* corresponding author, dtww{at}ucla.edu

	ABSTRACT

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This paper tests the hypothesis that salivary proteins and their counterpart mRNAs co-exist in human whole saliva. Global profiling of human saliva proteomes and transcriptomes by mass spectrometry (MS) and expression microarray technologies, respectively, revealed many similarities between saliva proteins and mRNAs. Of the function-known proteins identified in saliva, from 61 to 70% were also found present as mRNA transcripts. For genes not detected at both protein and mRNA levels, we made further efforts to determine if the counterpart is present. Of 19 selected genes detected only at the protein level, the mRNAs of 13 (68%) genes were found in saliva by RT-PCR. In contrast, of many mRNAs detected only by microarrays, their protein products were found in saliva, as reported previously by other investigators. The saliva transcriptome may provide preliminary insights into the boundary of the saliva proteome.

KEY WORDS: microarray • mass spectrometry • saliva proteome • saliva transcriptome • correlation analysis

	INTRODUCTION

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Human saliva contains informative components that can be used as diagnostic markers for human diseases. Our laboratory is using patient-based genome-wide and proteome-wide technologies to identify disease biomarkers from saliva. We have recently identified thousands of human mRNAs in saliva, using expression microarrays (Li et al., 2004a), and discovered salivary RNA markers for oral cancer detection. Four saliva mRNA biomarkers (OAZ-1, SAT, IL1b, and IL8) collectively exhibit a 91% sensitivity and specificity for human oral cancer (Li et al., 2004b).

We have recently conducted human saliva proteome analysis using mass spectrometry (Hu et al., 2004, 2005). Cataloguing of the total proteins in human saliva will form a solid foundation for disease biomarker discovery study. In this study, we hypothesized that proteins and their counterpart mRNAs co-exist in human saliva. We tested the hypothesis by performing correlation analysis of saliva proteomes and transcriptomes from three healthy volunteers. The salivary transcriptome may provide preliminary insights into the boundary of the saliva proteome.

	MATERIALS & METHODS

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Saliva Sample Collection and Processing
Unstimulated saliva was collected between 9 a.m. and 10 a.m. according to published protocols (Navazesh, 1993). Participants were asked to refrain from eating, drinking, smoking, or oral hygiene procedures, and a water mouthrinse was required prior to sample collection. The study population was composed of six males and four females, with an average age of 42 yrs (range, 32–55 yrs). The following inclusion criteria were used: age 30 yrs, and no history of malignancy, immunodeficiency, autoimmune disorders, hepatitis, HIV infection, or smoking. Each participant underwent a physical examination by a dentist, to ensure that no suspicious mucosal lesion or inflammation was present in the oral cavity. The oral mucosa appeared healthy, without erythema and epithelial desquamations. There was also no active decay observed. A male volunteer (age, 33 yrs) was used for comparative saliva proteome and transcriptome analysis. All participants signed the institutional-review-board-approved consent form. RNase inhibitor (Superase-In, Ambion Inc., Austin, TX, USA) and protease inhibitor cocktail (Sigma, St. Louis, MO, USA) were immediately added to the saliva. The samples were centrifuged at 2600 g for 15 min (4°C), and the supernatant was aliquoted and stored at –80°C.

Saliva Proteome Analysis
Both "shotgun" and 2-D electrophoresis/MS (2-DE/MS) approaches were utilized for saliva proteome analysis of a single participant (Hu et al., 2005). For the "shotgun" approach, saliva samples (1 mL) were pre-fractionated with the use of Millipore ultracentrifuge filters (Millipore Corp., Billerica, MA, USA). Individual fractions were treated with 10 mM dithreitol for 30 min and then 50 mM iodoacetamide for 30 min. Afterward, each fraction was digested overnight with 100 ng trypsin at 37°C. The resulting peptide digests were then analyzed with LC-MS/MS (QSTAR^® Pulsar XL QqTOF-MS; LC Packings and Applied Biosystems, Sunnyvale, CA, USA) on an LC Packings PepMap C18 pre-column and C18 analytical column. For 2-DE/MS experiments, saliva proteins were sequentially separated by isoelectric focusing and SDS-PAGE, and were visualized with Sypro-Ruby (Molecular Probes, Eugene, OR, USA). Gel spots were then excised and digested for MALDI-MS analysis (Micromass-Waters, Beverly, MA, USA), with -cyano-4-hydroxycinnamic acid as the matrix. Database searching was performed with Mascot software (Matrix Science, London, UK).

RNA Isolation, Amplification, and HG-U133A Microarray Analysis
RNA was isolated from saliva supernatant with the use of a QIAamp Viral RNA kit (Qiagen, Valencia, CA, USA) as previously reported (Li et al., 2004a). Aliquots of RNA were treated with RNase-free DNase (DNase I-DNA-free, Ambion Inc., Austin, TX, USA) and then subjected to linear amplification in a RiboAmp^TM RNA Amplification kit (Arcturus, Mountain View, CA, USA). We then used the Human Genome U133A Array (Affymetrix, Santa Clara, CA, USA) to perform gene expression analysis. The arrays were scanned, and the fluorescence intensities were measured by Microarray Suite 5.0 software (Affymetrix). The data were imported into DNA-Chip Analyzer software (Affymetrix) for normalization and model-based analysis (Li and Wong, 2001). A detection p-value was obtained for each probe set, and any probe sets with p < 0.04 were assigned as "present", indicating that the matching gene transcript was reliably detected (Affymetrix, 2001). The raw data were then exported to Microsoft Excel software for data-sorting and -mining.

RT-PCR
We performed RT-PCR to validate a subset of selected transcripts that were assigned as "absent" on all 10 microarrays. Total RNA was reverse-transcribed in 40 µL of reaction mixture containing 2.5 U of Moloney murine leukemia virus reverse transcriptase and 50 pmol of random hexanucleotides (Applied Biosystems Inc.) at 42°C for 45 min. Oligonucleotide primers for PCR were obtained from Fisher Scientific (Tustin, CA, USA) (Table). Amplification of the complementary DNA (cDNA) was carried out by 50 cycles at 95°C for 20 sec, customized annealing Tm for 30 sec, and at 72°C for 30 sec, followed by a final extension cycle at 72°C for 7 min. Specificity of the PCR products was verified by the predicted size and by restriction digestion. To establish the specificity of the responses, we used negative controls in which either input RNA or the reverse transcriptase was omitted. As a positive control, mRNA was extracted from total salivary gland RNA (Clontech, Palo Alto, CA, USA).

	RESULTS

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View larger version (10K): [in this window] [in a new window]   Figure 1. 2-D virtual display (pI vs. log Mr) of all identified proteins in human saliva (A) (n = 1), as well as the proteins complementary to the Normal Saliva Core Transcriptome list (B) (n = 10).

Normal Saliva Core Transcriptome (NSCT)
We have profiled the saliva mRNA of 10 normal individuals using the U133A arrays. On average, 3143 ± 665 probe sets (p < 0.04, n = 10) were assigned as present (Li et al., 2004a). Two hundred seven probe sets, representing 185 genes, were detected among all 10 participants (detection p < 0.01). Using the same criterion, we found 570 genes present in 8/10 (80%) arrays, and 417 genes in 9/10 (90%) arrays. Among these, 49 and 37 salivary mRNAs, respectively, were found to be present in saliva at protein levels as determined by proteomic approaches. The genes present among all 10 arrays (100%) are referred to as "Normal Saliva Core Transcriptome (NSCT)" (APPENDIX). Their nucleotide sequences were virtually translated into amino acid sequences, and then the corresponding pI and molecular weights were displayed in a virtual 2-D format (Fig. 1B). These core genes were evenly distributed across a wide pI range (pI 3.7–12.1), but their Mr fell into a relatively narrow range, from around 10 to 100 kDa. Of the 185 core mRNAs, 43 (23%, highlighted in the APPENDIX) were also found present at the protein level in the 3 saliva samples examined by proteomics approaches.

Co-existence of Saliva Protein and mRNA
The saliva protein and mRNA lists obtained from the three participants’ saliva were compared, and a co-existence phenomenon was observed. In Participant 1, 309 saliva proteins were identified, including 220 proteins with known biological functions and 89 hypothetical proteins without annotated function. Microarray profiling indicated that 154 (154/220, 70%) proteins with known functions were detected at the mRNA level, and the remaining 66 were not detectable. Similarly, 61% (130/213) and 65% (149/229) of function-known saliva proteins identified in Participants 2 and 3, respectively, were also found to "co-exist" with their saliva mRNAs.

Because microarray profiling may give false-negative results pertaining to the detected absence of saliva mRNA, we proceeded to test if the "undetectable" mRNAs were actually absent or present in saliva. We used RT-PCR to validate the presence of 9 mRNAs randomly selected from the "undetectable" 66 mRNAs from Participant 1. These mRNAs included serum albumin (ALB), heat-shock 60-kDa protein 1 (HSPD1), defensin, alpha-3 (DEFA3), neutrophil defensin 3 (HNP-3), integrin, beta 6 (ITGB6), kallikrein 1 (KLK1), ribosomal protein S11 (RPS11), transferrin (TF), and zinc-alpha-2-glycoprotein precursor (LOC340333) (Table). RT-PCR results indicated that mRNAs of HSPD1, DEFA3, ITGB6, KLK1, RPS11, TF, and HNP-3 were actually present in the saliva from Participant 1, and that LOC340333 and ALB mRNAs were undetectable (Fig. 2). These results suggested that the co-existence of salivary proteins and their mRNAs may reach a higher extent than the 70% (154/220) obtained by comparison of the proteomics and microarray outcomes. Of the remaining 66 (30%) salivary mRNAs that were undetectable by microarray, 7/9 (78%) could be independently detected by RT-PCR. This suggested that ~ 51 (78% of 66) additional saliva proteins may have a corresponding mRNA co-existing in saliva. Therefore, we may predict a co-existence rate of 93% (205/220) for saliva proteins and their counterpart saliva mRNAs. Similarly, we were able to validate 3 out of 5 randomly selected genes initially undetectable by microarray profiling in Participant 2 or Participant 3. RT-PCR analysis indicated that mRNAs of transcobalamin I (TCN1), myeloperoxidase (MPO), and hemopexin (HPX) were actually present in the saliva from Participant 2, whereas hepatocellular carcinoma-associated protein TB6 (PIGR) and alpha-1-antitrypsin (SERPINA1) mRNAs were undetectable. Meanwhile, in Participant 3, cystatin SA (CYST2), carbonic anhydrase IV (CA4), and HPX were detected, whereas cystatin SN (CYST1) and SERPINA1 were not (Figs. 2B, 2C).

View larger version (54K): [in this window] [in a new window]   Figure 2. RT-PCR validation of randomly selected mRNAs in Participant 1 (A), Participant 2 (B), and Participant 3 (C). (A) Lanes 1 and 20 are DNA ladders. Saliva RNAs were detected in lanes 2 (HSPD1), 4 (DEFA3), 6 (ITGB6), 8 (KLK1), 10 (RPS11), 12 (TF), and 18 (HNP-3). LOC340333 (lane 14) and ALB (lane 16) were not detectable. Total salivary gland RNA (Clontech, Palo Alto, CA, USA) was used as a positive control, shown in lanes 3 (HSPD1), 5 (DEFA3), 7 (ITGB6), 9 (KLK1), 11 (RPS11), 13 (TF), 15 (LOC340333), 17 (ALB), and 19 (Defensin, HNP-3), respectively. Negative controls were used in which input RNA was omitted, or in which RNA was used but reverse-transcriptase was omitted (data not shown). (B) Lanes 1 and 12 are DNA ladders. Lane 2 (TCN1), lane 4, (PIGR), lane 6 (MPO), lane 8 (HPX), and lane 10 (SERPINA1) are PCR products from total salivary gland RNA, which served as positive controls. Corresponding mRNAs of TCN1 (lane 3), MPO (lane 7), and HPX (lane 9) were detected in the participant’s saliva, but PIGR (lane 5) and SERPINA1 (lane 11) were not detected. (C) Lane 2 (CYST1), lane 4 (CYST2), lane 6 (CA4), lane 8 (HPX), and lane 10 (SERPINA1) are positive controls. CYST2 (lane 5), CA4 (lane 7), and HPX (lane 9) were detected in saliva, but CYST1 (lane 3) and SERPINA1 (lane 11) were not detectable.

	DISCUSSION

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Many genes were found only at either the protein or the mRNA level. For instance, proteomics revealed all salivary cystatin isoforms; however, microarray detected only 2 mRNAs from this gene family. This may be simply because there are no matching probe sets on the U133A array for other cystatins. Conversely, microarray revealed many ribosomal mRNAs, while proteomics discovered only some of the ribosomal proteins. It is likely that our preliminary MS analysis yielded only a subset of the entire saliva proteome. An additional pre-fractionation strategy can help expand the catalogue of saliva proteins. Currently, for a specific gene, validation at either the protein or the mRNA level is required for accurate RNA-protein correlation analysis.

In Participant 1, our analysis indicated that 70% (154/220) of the function-known saliva proteins had a corresponding saliva mRNA detectable by microarray. Of the remaining 66 (30%) genes, 9 candidates were selected for detection of the corresponding mRNA by RT-PCR (Table). These mRNA candidates were not found by microarray profiling, possibly because of the absence of matching probe sets on the U133A array. Seven of 9 genes were detectable by RT-PCR in saliva from Participant 1 (Fig. 2A), suggesting a higher correlation between saliva mRNAs and proteins than we obtained from proteomics and microarray profiling. Of the remaining 66 (30%) salivary mRNAs that were undetectable by microarray, 7/9 (78%) could be independently detected by RT-PCR. This suggests that ~ 51 (78% of 66) additional saliva proteins actually have a corresponding mRNA co-existing in saliva, and predicts a co-existence rate of 93% (205/220) for saliva proteins and their counterpart mRNAs. Similarly, further RT-PCR analysis suggested that there was a higher co-existence rate (85% for Participant 2 and 86% for Participant 3) than the one obtained from direct correlation of proteomics and microarray data (61% for Participant 2 and 65% for Participant 3).

The proteins discovered by proteomics represent only a partial list of all proteins in whole saliva. Many saliva proteins at lower concentrations remain to be identified. Therefore, only 7% of saliva mRNAs detected by microarray profiling were found to be present in the protein list. But this does not necessarily mean that the remaining (93%) mRNAs lack counterpart proteins. Several genes—including calmodulin, ß-2-microglobulin, epidermal growth factor, ferritin, fibroblast growth factor, heat-shock protein 70, hepatocyte growth factor, histones, interleukin-2, interleukin-6, interleukin-8, superoxide dismutase, etc.—were detected by microarray, but not by proteomic profiling. Other investigators have previously found these proteins to be present in human saliva (Balekjian and Longton, 1973; Law and Henkin, 1986; Maddali et al., 1995; Trubnikov et al., 1998; Kagami et al., 2000; Streckfus et al., 2001; Nagler et al., 2002; Ohshima et al., 2002; Fabian et al., 2003; Eckley et al., 2004). In conclusion, comparative analysis of the saliva proteome and transcriptome from three healthy individuals allowed us to conclude that many salivary proteins and mRNA are concordantly present in human saliva. This is an important observation, since we, and others, are actively deciphering the human salivary proteome. One of the problems inherent in saliva proteome analysis is how to define the boundary of the proteome and decide the ’finish line’ for the analysis. Considering the relatively high co-existence rate for saliva proteins and their counterpart mRNAs, the salivary transcriptome may serve as a good indicator of the diversity and range of the salivary proteome, and can be used as a reference guideline for human saliva proteome analysis. The specificity and coverage of RNA and protein profiling technologies need to be improved to yield more accurate and complete RNA-protein correlation analysis. In addition to high-throughput MS and microarray profiling, complementary validation methods, such as Western blots/ELISA or RT-PCR, will be required in the conduct of RNA-protein correlation studies.

	ACKNOWLEDGMENTS

 
This work was supported by NIH U01 DE015018 (to D.T. Wong) and NIH U01 U01DE016275 (to D.T. Wong and J.A. Loo), and by a faculty seed grant from the UCLA School of Dentistry (to S. Hu). We thank Drs. Jim Kerwin, Tianwei Yu, and Weihong Yan and Mr. Shawn Than for editing the manuscript and uploading the data to the UCLA human salivary proteome Web site (www.hspp.ucla.edu).

	FOOTNOTES

 
A supplemental appendix to this article is published electronically only at http://www.dentalresearch.org.

Received June 2, 2005; Last revision July 24, 2006; Accepted September 6, 2006

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This Article Abstract Figures Only Full Text (PDF) Appendix Services Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (5) Citing Articles via Google Scholar Google Scholar Articles by Hu, S. Articles by Wong, D.T. Search for Related Content PubMed PubMed Citation Articles by Hu, S. Articles by Wong, D.T.